Geology topics

David T. Barnett

Publications and source records attributed to David T. Barnett.

7 recordsLinked to original sources

USGS2019

The plant diversity sampling design for The National Ecological Observatory Network

The National Ecological Observatory Network (NEON) is designed to facilitate an understanding of the impact of environmental change on ecological systems. Observations of plant diversity—responsive to changes in climate, disturbance, and land use, and ecologically linked to soil, biogeochemistry, and organisms—result in NEON data products that cross a range of organizational levels. Collections include samples of plant tissue to enable investigations of genetics, plot‐based observations of incidence and cover of native and non‐native species, observations of plant functional traits, archived vouchers of plants, and remote sensing airborne observations. Spatially integrating many ecological observations allows a description of the relationship of plant diversity to climate, land use, organisms, and substrates. Repeating the observations over decades and across the United States will iteratively improve our understanding of those relationships and allow for the testing of system‐level hypotheses as well as the development of predictions of future conditions.

Ecosphere↗

USGS2017

Forecasting weed distributions using climate data: a GIS early warning tool

The number of invasive exotic plant species establishing in the United States is continuing to rise. When prevention of exotic species from entering into a country fails at the national level and the species establishes, reproduces, spreads, and becomes invasive, the most successful action at a local level is early detection followed eradication. We have developed a simple geographic information system (GIS) analysis for developing watch lists for early detection of invasive exotic plants that relies upon currently available species distribution data coupled with environmental data to aid in describing coarse-scale potential distributions. This GIS analysis tool develops environmental envelopes for species based upon the known distribution of a species thought to be invasive and represents the first approximation of its potential habitat while the necessary data are collected to perform more in-depth analyses. To validate this method we looked at a time series of species distributions for 66 species in Pacific Northwest, and northern Rocky Mountain counties. The time series analysis presented here did select counties that the invasive exotic weeds invaded in subsequent years, showing that this technique could be useful in developing watch lists for the spread of particular exotic species. We applied this same habitat-matching model based upon bioclimaric envelopes to 100 invasive exotics with various levels of known distributions within continental U.S. counties. For species with climatically limited distributions, county watch lists describe county-specific vulnerability to invasion. Species with matching habitats in a county would be added to that county's list. These watch lists can influence management decisions for early warning, control prioritization, and targeted research to determine specific locations within vulnerable counties. This tool provides useful information for rapid assessment of the potential distribution based upon climate envelopes of current distributions for new invasive exotic species.

Invasive Plant Science and Management↗

USGS2017

Ecology and space: A case study in mapping harmful invasive species

The establishment and invasion of non-native plant species have the ability to alter the composition of native species and functioning of ecological systems with financial costs resulting from mitigation and loss of ecological services. Spatially documenting invasions has applications for management and theory, but the utility of maps is challenged by availability and uncertainty of data, and the reliability of extrapolating mapped data in time and space. The extent and resolution of projections also impact the ability to inform invasive species science and management. Early invasive species maps were coarse-grained representations that underscored the phenomena, but had limited capacity to direct management aside from development of watch lists for priorities for prevention and containment. Integrating mapped data sets with fine-resolution environmental variables in the context of species-distribution models allows a description of species-environment relationships and an understanding of how, why, and where invasions may occur. As with maps, the extent and resolution of models impact the resulting insight. Models of cheatgrass ( Bromus tectorum ) across a variety of spatial scales and grain result in divergent species-environment relationships. New data can improve models and efficiently direct further inventories. Mapping can target areas of greater model uncertainty or the bounds of modeled distribution to efficiently refine models and maps. This iterative process results in dynamic, living maps capable of describing the ongoing process of species invasions.

Book chapter↗

USGS2016

Tick-, mosquito-, and rodent-borne parasite sampling designs for the National Ecological Observatory Network

Parasites and pathogens are increasingly recognized as significant drivers of ecological and evolutionary change in natural ecosystems. Concurrently, transmission of infectious agents among human, livestock, and wildlife populations represents a growing threat to veterinary and human health. In light of these trends and the scarcity of long-term time series data on infection rates among vectors and reservoirs, the National Ecological Observatory Network (NEON) will collect measurements and samples of a suite of tick-, mosquito-, and rodent-borne parasites through a continental-scale surveillance program. Here, we describe the sampling designs for these efforts, highlighting sampling priorities, field and analytical methods, and the data as well as archived samples to be made available to the research community. Insights generated by this sampling will advance current understanding of and ability to predict changes in infection and disease dynamics in novel, interdisciplinary, and collaborative ways.

Ecosphere↗

USGS2015

Modeling the present and future geographic distribution of the Lone star tick, Amblyomma americanum (Ixodida: Ixodidae ), in the continental United States

The Lone star tick ( Amblyomma americanum L.) is the primary vector for pathogens of significant public health importance in North America, yet relatively little is known about its current and potential future distribution. Building on a published summary of tick collection records, we used an ensemble modeling approach to predict the present-day and future distribution of climatically suitable habitat for establishment of the Lone star tick within the continental United States. Of the nine climatic predictor variables included in our five present-day models, average vapor pressure in July was by far the most important determinant of suitable habitat. The present-day ensemble model predicted an essentially contiguous distribution of suitable habitat extending to the Atlantic coast east of the 100th western meridian and south of the 40th northern parallel, but excluding a high elevation region associated with the Appalachian Mountains. Future ensemble predictions for 2061–2080 forecasted a stable western range limit, northward expansion of suitable habitat into the Upper Midwest and western Pennsylvania, and range contraction along portions of the Gulf coast and the lower Mississippi river valley. These findings are informative for raising awareness of A. americanum -transmitted pathogens in areas where the Lone Star tick has recently or may become established.

American Journal of Tropical Medicine and Hygiene↗

USGS2011

Using maximum entropy modeling for optimal selection of sampling sites for monitoring networks

Environmental monitoring programs must efficiently describe state shifts. We propose using maximum entropy modeling to select dissimilar sampling sites to capture environmental variability at low cost, and demonstrate a specific application: sample site selection for the Central Plains domain (453,490 km 2 ) of the National Ecological Observatory Network (NEON). We relied on four environmental factors: mean annual temperature and precipitation, elevation, and vegetation type. A “sample site” was defined as a 20 km × 20 km area (equal to NEON’s airborne observation platform [AOP] footprint), within which each 1 km 2 cell was evaluated for each environmental factor. After each model run, the most environmentally dissimilar site was selected from all potential sample sites. The iterative selection of eight sites captured approximately 80% of the environmental envelope of the domain, an improvement over stratified random sampling and simple random designs for sample site selection. This approach can be widely used for cost-efficient selection of survey and monitoring sites.

Diversity↗

USGS2007

The art and science of weed mapping

Land managers need cost-effective and informative tools for non-native plant species management. Many local, state, and federal agencies adopted mapping systems designed to collect comparable data for the early detection and monitoring of non-native species. We compared mapping information to statistically rigorous, plot-based methods to better understand the benefits and compatibility of the two techniques. Mapping non-native species locations provided a species list, associated species distributions, and infested area for subjectively selected survey sites. The value of this information may be compromised by crude estimates of cover and incomplete or biased estimations of species distributions. Incorporating plot-based assessments guided by a stratified-random sample design provided a less biased description of non-native species distributions and increased the comparability of data over time and across regions for the inventory, monitoring, and management of non-native and native plant species.

Environmental Monitoring and Assessment↗